High-Resolution Imaging and Micromotion Feature Extraction of Space Multiple Targets

In radar applications, different micromotion forms can be used as the basis of target recognition. However, the radar echo signal of multiple spatial targets is overlapping in the time-frequency and time-range domains, which increases the difficulty of micromotion feature extraction. In this article, a high-resolution imaging and micromotion feature extraction framework based on a multiple joint-domain radar tool is proposed to address this mixed signal. First, an accurate and suitable micromotion model of cone-shaped space multiple targets is built. Then, the 2-D adaptive regularized smoothed L0 norm algorithm based on sparse reconstruction is formulated to directly reconstruct the inverse synthetic aperture radar (ISAR) image. In addition, the range-frequency-time radar data cube can be extracted from the ISAR movie by the CLEAN algorithm. To solve the scattering point association problem in the radar data cube, a 3-D segmentation Viterbi algorithm is designed to extract the micromotion features. Finally, simulation and experiment results demonstrate the effectiveness of the proposed framework.